A Leading ITAD Company Employs Gen AI-Pricing to Maximize Value for End-of-Life Assets— Ignited “5 Million Dreams” with their Affordable Technology Program
Case Study
A Leading ITAD Company Employs Gen AI-Pricing to Maximize Value for End-of-Life Assets— Ignited “5 Million Dreams” with their Affordable Technology Program
About the Client
The Client is a leader in IT asset value recovery. They aim to be the best destination for enterprises, institutes, and OEMs to perform ITAD (IT assets disposition). But the company also goes a step beyond safe retirement of assets. Their refurbishment process recovers the highest possible value from the end-of-life assets. This value recovery is typically achieved by reselling the recertified assets through multiple channels (D2C, D2B, e-commerce marketplaces, and retailers). These affordable assets are given a second life as they are purchased by families otherwise caught in the digital divide.
Business Challenge
At the core of their operations lies a customer portal that allows enterprises to submit their asset details (serial numbers, model, condition) and accordingly receive pricing quotes. However, the client’s customers typically experienced delays (1-2 days) to receive an ideal quote for their end-of-life assets. This was because the pricing team manually computed prices relying on historical patterns and pricing information from competitors’ websites. The effort was significant given the large number of SKUs. Added to this, achieving pricing accuracy while factoring in many variables posed a significant challenge for the pricing team. Taken together, these factors contributed to operational inefficiencies and hindered their ability to scale their ITAD and value recovery business.
Trigent’s Solution
Empower the pricing team with a Gen AI-powered Pricing engine.
Use a case-based pricing strategy to arrive at the optimal price.
A real-time dashboard for internal teams to have strategic control over pricing decisions.
Solution Implementation
The Gen AI engine had primarily three components:
A scraping engine that fetches real-time market data (URLs and product details) from 16 different websites
A search catalog that categorizes the scraped data
ML+NLP-based similarity engine to arrive at a price match for end-of-life assets
Case-based pricing for arriving at a fair-market value.
Case 1: There is no match.
Case 2: There is a match but the price is out of bounds
In certain situations, there would be a product match but the price would be unreliable. In such cases, the system discards it and asks the Gen AI to predict a better price.
Case 3: There is a match, but the grades differ.
Case 4: The product and the grades match.
Conclusion
The case study highlights the ability of a ‘bolt-on’ Gen AI solution to unlock massive savings not just for the business, but also for its customers by recovering highest value from their retired assets. Giving the retired assets a new lease of life is a critical step in conquering the digital divide. The sections of populations rarely touched by digital transformation have been impacted through the affordable technology program. The client steers ahead to ignite a billion dreams through their new-life assets.
Client Benefits
- 99% reduction in Processing Time: The pricing computation that would otherwise take two weeks for 100 models (factoring in 25 variables) is performed by the engine in just 1 hour.
- 3X Acceleration in Asset Value Recovery: The intelligent pricing mechanism ensures that each end-of-life asset is resold at its optimal price. The customers’ appreciation of transparent pricing enabled a 3X acceleration of the refurbishment and value recovery business.
- Real-time Flexibility in Pricing Strategy: The system allows for dynamic formula adjustments to maintain competitive edge. Users can modify pricing rules based on demand surges, older products, and seasonal trends.
- Resource Optimization at scale: The real-time engine empowered the client to triple the scale of its asset value recovery, all while maintaining the same resource footprint and team size.
- 25% Uplift in Seasonal Revenues: The client increased its seasonal campaign revenues by 25%, thanks to the real-time dashboards which enabled strategic stock planning and proactive discounting.
- 5 Million Lives Impacted: By extending the life of assets, the client enabled 5 million underserved students to gain affordable access to digital technology. A giant leap towards advancing both digital equity and e-waste reduction.
Technology Stack
